“Big Data + Shipping” Constructs the Innovation Mode of Shipping Industry Chain

The combination of shipping and large data has not yet reached the stage of “subversion”, but with the deepening of large data applications, the traditional business models and emerging technologies will continue to increase the spark.

Recently, a famous Norwegian shipowner said that the shipping industry to learn to step (Uber) experience, the use of large data to create a new business model. Businesses with large data analytics to achieve business success are challenging traditional industries with a range of opportunities. Shipping industry, has always been a synonym for traditional industries, the current shipping industry where the big data went one step? Whether the ability to subvert the industry? In the new shipping environment, the big data will also affect the industry trend?

The Application of Big Data in Shipping

McKinsey’s definition of large data is: “a large scale in the acquisition, storage, management, analysis greatly beyond the traditional database software tools, a range of data collection capabilities.” In recent years, the big data effect turns the story of the traditional business model turns, the new business model emerging: from gifted, Alibaba Empire’s success, to the current and emerging technologies, such as industrial 4.0, intelligent manufacturing, unmanned technology deepen. It can be said that large data has become a global economic restructuring and an active factor.

Shipping industry is a century-old tradition of traditional industries. The impact of the new technology on the industry can be traced back to the application of computer technology, the speed of information transmission, the development of large-scale ships and port facilities to enhance the modernization of power at the time set off a huge shipping industry history. Today, “large data + shipping” will catch up with the application of computer technology in the history of shipping left a deep imprint it? To answer this question, the first question to be faced is the application of large data in the shipping industry how? Development to what extent?

Shanghai International Shipping Research Center, Xu Kai, director of information technology, told reporters that large data applications are divided into three types of shipping: The first is the application of real-time data, such as through the navigation plan, ship speed, ship exhaust, meteorological ocean current data Time calculation of the economic speed of the captain to provide energy-saving emission reduction recommendations; through the channel throughput statistics, real-time calculation of channel congestion, and possible maritime risk to provide early warning; on the shipping market supply and demand and commodity trade data Of the analysis of the industry to assess the health of market operations, providing economic forecasting of economic operation of the economy and so on. The second category is the application of historical data analysis, such as through the shipping business, operational data mining, forecasting for the shipping market, route arrangements, fleet construction of new vessels, second-hand sale, risk control, own capacity and rental structure costs and Profit analysis and other services; through the shipping business platform in the production and operation of data analysis, can tap new business opportunities and create new industry value; can maritime accident-related historical information analysis, that may cause accidents High incidence of the main factors. The third category is the application of predictive analysis of future developments. For example, based on available historical data and real-time data, forecast the distribution of future regional shipping capacity, cargo inventory of major ports, the trend of trade flows of major commodities, Delay in arrival of the ship early warning and so on. Large data in the shipping industry a wide range of influence, the whole industry chain stakeholders, from shipyards, shipowners, brokers, shippers, and even banks, insurance, are gradually exploring the use of large data products to improve its decision-making and management system. But it is worth noting that the current application of these applications have not been fully realized, only some are skilled application, a considerable part of the only stay in the beginning and not yet set foot stage.

The comparison between the optimal step and the shipping configuration scheduling is made. He said that the reason why the optimal step to successfully achieve optimal allocation of scheduling is mainly based on three reasons: One is that each driver can be installed to locate real-time location of the vehicle APP (drivers, real-time vehicle data); second mobile phone users to submit their own The detailed actual location and destination requirements (customer demand data); Third, the city map to calculate the best path (based on road network based data), and excellent step before departure to calculate the required payment amount, the final fare is not Will be a big difference before and after. This is the excellent step into the market before the car can not match the scheduling. Now we will be gifted success factors into the shipping, to see whether the ship operation and scheduling to plan. It is also necessary to have a three-pronged foundation: to be able to master the information of the pallets and pallets; to be able to grasp the exact location of real-time operation of the ship and cargo loading; whether to master the sea anchorage, berth, berth, channel conditions, sea road network Such as the integration of geographic data. Unfortunately, there is currently no agency or company to collect all of the above information.

This proves from a certain extent, the impact of large data range, but not far-reaching, is still the primary stage of development. But this also shows that shipping large space for the development of large data. The current shipping industry has accumulated a large amount of shipping information resources, with the shipping data concept “shipping business, management, supervision and other fields of mass data” one of the basic conditions, and part of a large data-based applications have been The use of shipping data and intelligence services in the field of trade and financial research, the construction of online electronic business platform has been the domestic container line booking and domestic bulk cargo The emergence of online charter platform, which all foreshadowed a moment ready to subvert the traditional shipping industry chain ecological environment of the revolution is quietly brewing. The future if further into the “scale of the effective integration of data, storage, processing, query, analysis of related technologies and solutions,” the deepening of its imagination is huge.

Hot spots in the first breakthrough

The combination of shipping and large data has not yet reached the stage of “subversion”, but with the deepening of large data applications, the traditional business models and emerging technologies will continue to increase the spark. Billion sea blue shipping analyst Lin Shu-lai that, with the impact of large data on the shipping industry gradually deepened, is expected to subvert the shipping industry chain will be the whole of some of the traditional business model and the actual operational mode of operation, will make this traditional The industry more efficient, more and more transparent information, the shipping industry chain, the entire ecological environment will be because of these changes to reconstruction. In the near future is expected to be able to grow rapidly in the following areas.

The overall downturn in the shipping industry, the chain of many companies have been “kicked” out, Baotuan heating is undoubtedly the current and the future for quite some time the main theme of the enterprise, large data to the information platform to appear in a certain extent, harmony Chain, the formation of the shipper, the carrier, the consignee, freight forwarding, ports and other service sectors of the one-stop upstream and downstream “Union”, the trend of the judgments have been generally recognized by the industry. Xu Kai told reporters, both horizontal alliance between the same type of enterprise, or along the supply chain or industrial chain of vertical integration of enterprises, the basis for cooperation is the need to establish data collection and data sharing mechanism, which is the alliance of enterprises Cooperative operation of the basic conditions. In November this year by the China Shipowners Association, China International Freight Forwarders Association, China Port Association, China Port Association 5 units signed the “international shipping cooperation mechanism”, to some extent to achieve the Chinese shipping industry, the whole industry chain cooperation, The above view.

Port is an important gateway to international trade channel, big data in the future will further accelerate the pace of port interoperability and intelligent. The current supply chain is attracting much attention. The strength of science and technology, the large-scale ships and the wider port services mean that the port function has been diversified and become an important node of interconnection and interconnection. Xu Kai expects that by 2030, will be a port as a unit of large data centers, centralized storage of port of material generated by a large number of data, the terminal information resources will focus on the unified management of the port, the port to achieve information exchange between the domestic Major shipping centers will be built into large data centers and distributed data storage. Realization of interconnection is the future port of comprehensive competitiveness-oriented.

Big Data will be able to provide more transparent and tangible operational data in terms of financial credit in the future. Ship is one of the world’s most capital-intensive industries, and the ship assets as floating assets, the assessment is difficult, so banks in the shipping loan, the credit, guarantee under the foot work. In short, the credit refers to the bank to provide direct financial support to customers, or customers in the economic activities of the credit to a third party to guarantee behavior. Banks generally have to go through the project, communicate the completion of the relevant terms of the list, the project evaluation, complete the credit review, lending, lending and tracking several steps. Big data can be effectively used, the future can be more accurate and transparent information. Lin believes that the future of large data will be further application. In assessing the risk of ship financing, it is necessary to evaluate the past operational condition of the ship. The method of large data can be used to restore the ship’s operating condition and monitor the current operation of the ship. In case of any unusual situation, Alarm, than the traditional financial credit more close to the actual situation of the ship business.

Not only that, large data applications can optimize the operation of the ship. Lin Shu-lai, said the actual operation of the ship, through the route information, historical meteorological and hydrological information, the actual monitoring of real-time ship conditions and the navigation process of the external environment, the use of large data technology can achieve the ship’s optimal route, Speed ​​of choice, save fuel, reduce emissions and so on. In addition, it is also possible to predict the volume of trade on the future routes by using the data of precipitation and other variables to predict the throughput of each port, to arrange the capacity of ships between ports in advance, and to improve the operational efficiency of ships. Blocking Hong Kong, the phenomenon of stranded port.

Depth application long way to go

Clearly, the future of large data on the shipping market will gradually expand and deepen the impact of the global economic slowdown, the shipping industry is facing enormous challenges of survival, while cloud computing, Internet of things and the rapid development of large data indeed to the shipping industry Brought about a turning point, but there are some obstacles to the growth needs of further breakthroughs. Xu Kai and Lin to agree that the current shipping industry in the application of large data there are several issues to be gradually break through and improve.

First of all, for the shipping industry, the data generated by different sources, then the integration of large data will inevitably encounter “format” different issues. The vast amount of data generated by the shipping industry may be related to the bill of lading data related to the ship, ship operation-related navigation data, equipment data, there is a large body of standard lax, fragmented, incomplete data, statistical caliber is not consistent problem. So when finishing the need for manual conversion through special software, resulting in the delay and inefficiency of information transmission. So the establishment of a unified one of the data format standards for shipping large data development problems to be solved. Second, the information island effect is still relatively obvious, large data required by the “open sharing” has not been accepted by the industry, so win-win situation is difficult to open multi-win. The reason is that by the system or proprietary management and other issues, some aspects of the industry chain is still enjoying the policy of the dividend, the power of their own change is not strong, not willing to upstream integration, do not want to integrate downstream, making It is difficult to obtain some of the key data, is not conducive to the establishment of the entire industrial chain information channel, it is necessary to establish a multi-win and mutually beneficial information sharing mechanism, so that information sharing from the information platform to obtain their own information, “Demand-pull” mechanism to establish information sharing platform. Third, the security risks of large data has not been eliminated, as a big obstacle to the development of data, a “level” has become the target of hackers. Experts also call on government departments to play a role, and actively explore and build regulatory and risk control system and legal environment. Fourth, lack of data analysis. Data analysis is the most important part of the whole process of shipping large data processing. There are many sources of large data in shipping, huge amount of data and complicated data relations. We want to realize the comprehensive integration of shipping data, efficient and flexible storage, accurate processing, Quick and easy query is very difficult. Finally, the shipping industry, the lack of large data talent is also a development bottleneck. Large data applications and the establishment is often a complex system, the demand for talent is complex and cross-border nature, not only to understand the shipping industry, but also to master the information technology, data processing and other technology, often set up such a team is Quite not easy. Now there is a new job called a large data analyst, the shipping industry for the needs of such talent in a period of time or the need for information from a higher degree of introduction of some industries.

“Encircling the wood, was born in the end; nine of the Taiwan, from the tired soil; thousands of miles of the trip began with a single step.” No matter how far the future shipping large data to go, but the practical step taken the most important step. Xu Kai believes that the collection of real hand data is the first step. For various reasons, the current conscious to do this is difficult to rely on e-commerce and e-government, and the need for enterprises, government departments in charge of multi-party cooperation. As for the collection method can be achieved in two ways, one is to let robots instead of people to collect data. The second is to process all of the business activities from line to line. The former is the best way to achieve is to rely on ship networking, sensors to collect, that is, things. The latter mainly rely on e-commerce, which includes e-government, including booking, chartering and ordering materials.

Step by step after the first step, you can continue to dig the depth of the value of large data, Xu Kai gives three recommendations: One is the shipping companies should be shipping data into business strategy. Data analysis can help companies understand the most basic of all their own forums, the right to guide the flow of capital, to understand consumer spending habits, providing accurate service, which is the core value of large data. For example, if the freight forwarding enterprises through effective means of monitoring the transport of large data means the state of goods, when there is similar to the Hanjin collapse of the goods can not arrive on time, the situation can be timely pre-warning and early warning, You can take the initiative in response strategies. The second is to focus on large data on the industry’s resource allocation optimization. Zhoushan to provide maritime ship bonded fuel supply, for example, in Zhoushan to build international maritime service base under the policy of refueling prices in Singapore and the gap is already not much, but there are still many people “far away” to refuel and then return to Singapore , Part of the reason is that the existing fuel market supply price is not comprehensive, many owners do not understand the latest Zhoushan fuel prices, while scattered barge lack of large data under the guidance of the unified scheduling, but also makes the fuel supply service does not form a market Together. Correct use of large data analysis, reasonable and intelligent deployment of ships, one can avoid the “fly”, the other can simplify the customs supervision procedures, conservation of government regulatory resources. The third is concerned about the potential value of large data brought about by the value of shipping data may be in the field of trade, finance. In the case of oil transportation, crude oil can go through a period of more than half a month from loading to unloading. During this period, the volatility of crude oil market can bring some commercial value. Meanwhile, it will bring interest to the owner, hedge fund and investment enterprise.

Lin also suggested that for enterprises, the industry should be aware of the environment, grasp the opportunity of intelligent wave, the use of large data methods to optimize management decisions, improve operational efficiency, in the conditional conditions, Integration of resources to explore new business models; government, should advance with the times, the industry changes to a certain period of time, can improve the overall social efficiency and information security on the basis of dare to break administrative control, To own exclusive information resources for the advantage, to create a fair.